Python中的 numpy.array_equiv()
numpy.array_equiv(arr1, arr2) :此逻辑函数检查两个数组是否具有相同的元素和形状是否一致。
形状一致意味着它们具有相同的形状,或者可以广播一个输入数组以创建与另一个相同的形状。
参数 :
arr1 : [array_like]Input array, we need to test.
arr2 : [array_like]Input array, we need to test.
返回 :
True, if both arrays are equivalent; otherwise False
代码:解释工作
# Python program explaining
# array_equiv() function
import numpy as np
# input
arr1 = np.arange(4)
arr2 = [7, 4, 6, 7]
print ("arr1 : ", arr1)
print ("arr2 : ", arr2)
print ("\nResult : ", np.array_equiv(arr1, arr2))
arr1 = np.arange(4)
arr2 = np.arange(4)
print ("\n\narr1 : ", arr1)
print ("arr2 : ", arr2)
print ("\nResult : ", np.array_equiv(arr1, arr2))
arr1 = np.arange(4)
arr2 = np.arange(5)
print ("\n\narr1 : ", arr1)
print ("arr2 : ", arr2)
print ("\nResult : ", np.array_equiv(arr1, arr2))
a = np.array_equiv([1, 2], [[1, 2, 1, 2], [1, 2, 1, 2]])
b = np.array_equiv([1, 2], [[1, 2], [1, 2]])
print ("\n\na : ", a)
print ("\nb : ", b)
输出 :
arr1 : [0 1 2 3]
arr2 : [7, 4, 6, 7]
Result : False
arr1 : [0 1 2 3]
arr2 : [0 1 2 3]
Result : True
arr1 : [0 1 2 3]
arr2 : [0 1 2 3 4]
Result : False
a : False
b : True
参考 :
https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.array_equiv.html#numpy.array_equiv
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